155 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs at Zintellect
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development of artificial intelligence (AI), machine learning (ML) and large language models (LLMs) to help promote business intelligence in the Agency (e.g., interactive AI expert systems). Integration of AI
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are offered an opportunity for an independent research project using lab data to gain experience conducting ecological data analysis, manuscript writing, and publishing in peer-reviewed journals. Learning
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development. You will gain experience researching advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition, and participating in developing standardized
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to unravel key indicators of biological relevance during seed quality testing procedures and contribute to a healthy national and international seed trade economy. Learning Objectives: Under guidance of a
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documenting progress on data processing. Opportunities may also be available to participate in field data collection at various locations in the Pacific Northwest. Learning Objectives: As an educational
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plants. The participant will learn and use multiple molecular biology, synthetic biology and plant biotechnology related tools and techniques including plasmid vector design and assembly, plant genetic
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promoters. Digital Phenotyping: Application of hyperspectral imaging and advanced imaging tools to detect disease traits beyond the visible spectrum. AI-Driven Data Analysis: Leveraging machine learning
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Applied statistics Network routing Agent-based simulation Behavioral economics Game theory Decision theory Machine learning Artificial intelligence Where will I be located? Both local and remote
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assays from method development to experimental or test sample analysis including the process of method validation. Learning Objectives: Computational: Through this opportunity you will; Establish
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regions will be evaluated for features such as signatures of selection or diversifying or purifying selection, around genes and regions of agricultural importance. Learning Objectives: The participant will